contagion   435

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[1905.10738] Interacting Urns on a Finite Directed Graph
"Consider a finite directed graph G=(V,E) and place an urn with balls of two colours: white and black, at each node at time t=0. The urns evolve, in discrete time, depending upon a common replacement matrix R and the underlying graph structure. At each time-step, urns reinforce their neighbours according to a fixed replacement matrix R. We study asymptotic properties of the fraction of balls of either colour and obtain limit theorems for general replacement matrices. In particular, we show that if the reinforcement is not of what we call {P}ólya-type, there is always a consensus, almost surely, with Gaussian fluctuations in some regimes. We also prove that for {P}ólya-type replacements, the fraction of balls of either colour, in each urn, converges almost surely and that this limit is same for every urn. One of the motivations behind studying this model and choosing the replacement matrices comes from opinion dynamics on networks, where opinions are rigid and change slowly with influence from the neighbours."
to:NB  contagion  networks  path_dependence  interacting_particle_systems  voter_model 
29 days ago by cshalizi
[1905.11204] A trust model for spreading gossip in social networks
"We introduce here a multi-type bootstrap percolation model, which we call T-Bootstrap Percolation (T-BP), and apply it to study information propagation in social networks. In this model, a social network is represented by a graph G whose vertices have different labels corresponding to the type of role the person plays in the network (e.g. a student, an educator, etc.). Once an initial set of vertices of G is randomly selected to be carrying a gossip (e.g. to be infected), the gossip propagates to a new vertex provided it is transmitted by a minimum threshold of vertices with different labels. By considering random graphs, which have been shown to closely represent social networks, we study different properties of the T-BP model through numerical simulations, and describe its implications when applied to rumour spread, fake news, and marketing strategies."
to:NB  contagion  epidemic_models  networks  re:do-institutions-evolve 
29 days ago by cshalizi
Trends in the Diffusion of Misinformation on Social Media
In recent years, there has been widespread concern that misinformation on social media is damaging societies and democratic institutions. In response, social media platforms have announced actions to limit the spread of false content. We measure trends in the diffusion of content from 569 fake news websites and 9,540 fake news stories on Facebook and Twitter between January 2015 and July 2018. User interactions with false content rose steadily on both Facebook and Twitter through the end of 2016. Since then, however, interactions with false content have fallen sharply on Facebook while continuing to rise on Twitter, with the ratio of Facebook engagements to Twitter shares decreasing by 60 percent. In comparison, interactions with other news, business, or culture sites have followed similar trends on both platforms. Our results suggest that the relative magnitude of the misinformation problem on Facebook has declined since its peak.
misinformation  disinformation  contagion  social_networks 
february 2019 by rvenkat
Social Space Diffusion: Applications of a Latent Space Model to Diffusion with Uncertain Ties - Jacob C. Fisher, 2019
"Social networks represent two different facets of social life: (1) stable paths for diffusion, or the spread of something through a connected population, and (2) random draws from an underlying social space, which indicate the relative positions of the people in the network to one another. The dual nature of networks creates a challenge: if the observed network ties are a single random draw, is it realistic to expect that diffusion only follows the observed network ties? This study takes a first step toward integrating these two perspectives by introducing a social space diffusion model. In the model, network ties indicate positions in social space, and diffusion occurs proportionally to distance in social space. Practically, the simulation occurs in two parts. First, positions are estimated using a statistical model (in this example, a latent space model). Then, second, the predicted probabilities of a tie from that model—representing the distances in social space—or a series of networks drawn from those probabilities—representing routine churn in the network—are used as weights in a weighted averaging framework. Using longitudinal data from high school friendship networks, the author explores the properties of the model. The author shows that the model produces smoothed diffusion results, which predict attitudes in future waves 10 percent better than a diffusion model using the observed network and up to 5 percent better than diffusion models using alternative, non-model-based smoothing approaches."
social_influence  social_networks  network_data_analysis  homophily  contagion  via:cshalizi 
february 2019 by rvenkat
[1811.10372] Disentangling sources of influence in online social networks
"Information propagation in online social networks is facilitated by two types of influence - endogenous (peer) influence that is dependent on the network structure and current state of each user and exogenous (external) which is independent of these. However, inference of these influences from data remains a challenge. In this paper we propose a methodology that yields estimates of both endogenous and exogenous influence using only a social network structure and a single activation cascade. We evaluate our methodology on simulated activation cascades as well as on cascades obtained from several large Facebook political survey applications. We show that our methodology is able to provide estimates of endogenous and exogenous influence in online social networks, characterize activation of each individual user as being endogenously or exogenously driven, and to identify most influential groups of users."
to:NB  to_read  contagion  social_influence  re:homophily_and_confounding  to_be_shot_after_a_fair_trial 
december 2018 by cshalizi
The Effect of Media Coverage on Mass Shootings | IZA - Institute of Labor Economics
"Can media coverage of shooters encourage future mass shootings? We explore the link between the day-to-day prime time television news coverage of shootings on ABC World News Tonight and subsequent mass shootings in the US from January 1, 2013 to June 23, 2016. To circumvent latent endogeneity concerns, we employ an instrumental variable strategy: worldwide disaster deaths provide an exogenous variation that systematically crowds out shooting-related coverage. Our findings consistently suggest a positive and statistically significant effect of coverage on the number of subsequent shootings, lasting for 4-10 days. At its mean, news coverage is suggested to cause approximately three mass shootings in the following week, which would explain 55 percent of all mass shootings in our sample. Results are qualitatively consistent when using (i) additional keywords to capture shooting-related news coverage, (ii) alternative definitions of mass shootings, (iii) the number of injured or killed people as the dependent variable, and (iv) an alternative, longer data source for mass shootings from 2006-2016."
to:NB  to_read  contagion  causal_inference  to_teach:undergrad-ADA  to_be_shot_after_a_fair_trial  previous_tag_was_in_poor_taste 
december 2018 by cshalizi
The Effect of Media Coverage on Mass Shootings | IZA - Institute of Labor Economics
Can media coverage of shooters encourage future mass shootings? We explore the link between the day-to-day prime time television news coverage of shootings on ABC World News Tonight and subsequent mass shootings in the US from January 1, 2013 to June 23, 2016. To circumvent latent endogeneity concerns, we employ an instrumental variable strategy: worldwide disaster deaths provide an exogenous variation that systematically crowds out shooting-related coverage. Our findings consistently suggest a positive and statistically significant effect of coverage on the number of subsequent shootings, lasting for 4-10 days. At its mean, news coverage is suggested to cause approximately three mass shootings in the following week, which would explain 55 percent of all mass shootings in our sample. Results are qualitatively consistent when using (i) additional keywords to capture shooting-related news coverage, (ii) alternative definitions of mass shootings, (iii) the number of injured or killed people as the dependent variable, and (iv) an alternative, longer data source for mass shootings from 2006-2016.

--Is it really this easy?
crime  contagion  social_influence  econometrics  causal_inference  i_remain_skeptical  media_studies 
november 2018 by rvenkat
Norms in the Wild - Paperback - Cristina Bicchieri - Oxford University Press
The philosopher Cristina Bicchieri here develops her theory of social norms, most recently explained in her 2006 volume The Grammar of Society. Bicchieri challenges many of the fundamental assumptions of the social sciences. She argues that when it comes to human behavior, social scientists place too much stress on rational deliberation. In fact, many choices occur without much deliberation at all. Bicchieri's theory accounts for these automatic components of behavior, where individuals react automatically to cues--those cues often pointing to the social norms that govern our choices in a social world

Bicchieri's work has broad implications not only for understanding human behavior, but for changing it for better outcomes. People have a strong conditional preference for following social norms, but that also means manipulating those norms (and the underlying social expectations) can produce beneficial behavioral changes. Bicchieri's recent work with UNICEF has explored the applicability of her views to issues of human rights and well-being. Is it possible to change social expectations around forced marriage, genital mutilations, and public health practices like vaccinations and sanitation? If so, how? What tools might we use? This short book explores how social norms work, and how changing them--changing preferences, beliefs, and especially social expectations--can potentially improve lives all around the world.

--To-do: compare with Ullmann-Margalit's work. Don't remember the exact connections...
book  norms  dynamics  social_behavior  homophily  contagion  social_influence  networks  social_networks  teaching 
november 2018 by rvenkat
[1810.03579] Long ties accelerate noisy threshold-based contagions
"Changes to network structure can substantially affect when and how widely new ideas, products, and conventions are adopted. In models of biological contagion, interventions that randomly rewire edges (making them "longer") accelerate spread. However, there are other models relevant to social contagion, such as those motivated by myopic best-response in games with strategic complements, in which individual's behavior is described by a threshold number of adopting neighbors above which adoption occurs (i.e., complex contagions). Recent work has argued that highly clustered, rather than random, networks facilitate spread of these complex contagions. Here we show that minor modifications of prior analyses, which make them more realistic, reverse this result. The modification is that we allow very rarely below threshold adoption, i.e., very rarely adoption occurs, where there is only one adopting neighbor. To model the trade-off between long and short edges we consider networks that are the union of cycle-power-k graphs and random graphs on n nodes. We study how the time to global spread changes as we replace the cycle edges with (random) long ties. Allowing adoptions below threshold to occur with order 1/n‾√ probability is enough to ensure that random rewiring accelerates spread. Simulations illustrate the robustness of these results to other commonly-posited models for noisy best-response behavior. We then examine empirical social networks, where we find that hypothetical interventions that (a) randomly rewire existing edges or (b) add random edges reduce time to spread compared with the original network or addition of "short", triad-closing edges, respectively. This substantially revises conclusions about how interventions change the spread of behavior, suggesting that those wanting to increase spread should induce formation of long ties, rather than triad-closing ties."
via:cshalizi  networks  contagion  teaching  for_friends 
october 2018 by rvenkat
Twitter
. wraps up with a line from , and a nod to the challenges of outbreak communication: "Nobo…
Contagion  from twitter_favs
september 2018 by andriak
Rapid-onset gender dysphoria in adolescents and young adults: A study of parental reports
Methods

Recruitment information with a link to a 90-question survey, consisting of multiple-choice, Likert-type and open-ended questions, was placed on three websites where parents had reported rapid onsets of gender dysphoria. Website moderators and potential participants were encouraged to share the recruitment information and link to the survey with any individuals or communities that they thought might include eligible participants to expand the reach of the project through snowball sampling techniques. Data were collected anonymously via SurveyMonkey. Quantitative findings are presented as frequencies, percentages, ranges, means and/or medians. Open-ended responses from two questions were targeted for qualitative analysis of themes.

Results

There were 256 parent-completed surveys that met study criteria. The adolescent and young adult (AYA) children described were predominantly female sex at birth (82.8%) with a mean age of 16.4 years. Forty-one percent of the AYAs had expressed a non-heterosexual sexual orientation before identifying as transgender. Many (62.5%) of the AYAs had been diagnosed with at least one mental health disorder or neurodevelopmental disability prior to the onset of their gender dysphoria (range of the number of pre-existing diagnoses 0–7). In 36.8% of the friendship groups described, the majority of the members became transgender-identified. The most likely outcomes were that AYA mental well-being and parent-child relationships became worse since AYAs “came out”. AYAs expressed a range of behaviors that included: expressing distrust of non-transgender people (22.7%); stopping spending time with non-transgender friends (25.0%); trying to isolate themselves from their families (49.4%), and only trusting information about gender dysphoria from transgender sources (46.6%).

Conclusion

Rapid-onset gender dysphoria (ROGD) describes a phenomenon where the development of gender dysphoria is observed to begin suddenly during or after puberty in an adolescent or young adult who would not have met criteria for gender dysphoria in childhood. ROGD appears to represent an entity that is distinct from the gender dysphoria observed in individuals who have previously been described as transgender. The worsening of mental well-being and parent-child relationships and behaviors that isolate AYAs from their parents, families, non-transgender friends and mainstream sources of information are particularly concerning. More research is needed to better understand this phenomenon, its implications and scope.

--- and the administrative and bureaucratic stupidity that followed
https://news.brown.edu/articles/2018/08/gender
debates  nature-nurture  social_influence  contagion  social_networks  sociology_of_science  gender_studies  social_construction_of_ignorance  university  academia  bureaucracy 
august 2018 by rvenkat
Centola, D.: How Behavior Spreads: The Science of Complex Contagions (Hardcover and eBook) | Princeton University Press
"New social movements, technologies, and public-health initiatives often struggle to take off, yet many diseases disperse rapidly without issue. Can the lessons learned from the viral diffusion of diseases be used to improve the spread of beneficial behaviors and innovations? In How Behavior Spreads, Damon Centola presents over a decade of original research examining how changes in societal behavior--in voting, health, technology, and finance—occur and the ways social networks can be used to influence how they propagate. Centola's startling findings show that the same conditions accelerating the viral expansion of an epidemic unexpectedly inhibit the spread of behaviors.
"While it is commonly believed that "weak ties"—long-distance connections linking acquaintances—lead to the quicker spread of behaviors, in fact the exact opposite holds true. Centola demonstrates how the most well-known, intuitive ideas about social networks have caused past diffusion efforts to fail, and how such efforts might succeed in the future. Pioneering the use of Web-based methods to understand how changes in people's social networks alter their behaviors, Centola illustrates the ways in which these insights can be applied to solve countless problems of organizational change, cultural evolution, and social innovation. His findings offer important lessons for public health workers, entrepreneurs, and activists looking to harness networks for social change."
to:NB  books:noted  contagion  social_influence  social_networks  centola.damon  sociology  re:homophily_and_confounding 
july 2018 by cshalizi

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